Characterizing trajectories of cognitive functioning in older adults with schizophrenia: does method matter?
Wesley K Thompson1, Gauri N Savla, Ipsit V Vahia
1Stein Center for Research on Aging, 9500 Gilman Drive, University of California San Diego, La Jolla, CA 92093-0664, USA. wkthompson@ucsd.edu
Schizophrenia Research
|December 11, 2012
Summary
Schizophrenia patients show varied cognitive trajectories, with some stable and others declining. Identifying these distinct patient groups aids in targeted interventions and understanding disease heterogeneity.
Area of Science:
- Neuroscience
- Psychiatry
- Cognitive Science
Background:
- Clinical outcomes in schizophrenia exhibit heterogeneity due to multi-level factors.
- Understanding variation in schizophrenia patients versus healthy controls aids etiology and subtype identification.
Purpose of the Study:
- To identify distinct subclasses of schizophrenia patients based on cognitive trajectories.
- To analyze factors associated with class membership and cognitive correlates.
Main Methods:
- Growth mixture models were used to analyze cognitive trajectories over 3.5 years.
- 201 schizophrenia patients and 67 healthy controls participated.
- Post hoc analyses examined correlates of identified classes.
Main Results:
- Three latent classes emerged: stable cognition (Class 1), modest decline (Class 2), and rapid decline (Class 3).
- Class 1 comprised 50% schizophrenia patients and 85% healthy controls.
- Classes 2 and 3 (schizophrenia patients) were linked to worse negative symptoms and board and care facility residence.
Conclusions:
- The study differentiates between cognitive stability and decline in schizophrenia.
- Characterizing cognitive heterogeneity is crucial for interventions and patient management.
- Analyses must be sensitive to both between- and within-patient heterogeneity.
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